Jonathan Chapman, M. Dean, Pietro Ortoleva, E. Snowberg, Colin Camerer
{"title":"Econographics","authors":"Jonathan Chapman, M. Dean, Pietro Ortoleva, E. Snowberg, Colin Camerer","doi":"10.1086/723044","DOIUrl":null,"url":null,"abstract":"We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision-making. We elicit 21 behaviors, using an incentivized survey on a representative sample (n=1,000) of the US population. Our data show a clear and relatively simple structure underlying the correlations between these measures. Using principal components analysis, we reduce the 21 variables to six components corresponding to clear clusters of high correlations. We examine the relationship between these components, cognitive ability, and demographics. Common extant theories are not compatible with all the patterns in our data.","PeriodicalId":289840,"journal":{"name":"Journal of Political Economy Microeconomics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Political Economy Microeconomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1086/723044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We study the pattern of correlations across a large number of behavioral regularities, with the goal of creating an empirical basis for more comprehensive theories of decision-making. We elicit 21 behaviors, using an incentivized survey on a representative sample (n=1,000) of the US population. Our data show a clear and relatively simple structure underlying the correlations between these measures. Using principal components analysis, we reduce the 21 variables to six components corresponding to clear clusters of high correlations. We examine the relationship between these components, cognitive ability, and demographics. Common extant theories are not compatible with all the patterns in our data.